conda activate chart_reader
nohup python train_extraction.py --cfg_file KPDetection --data_dir "./data/EC400K_ChartLLM/clsdata(1031)/cls" --cache_path "./data/cache" >> log/INFO.log 2>>log/ERROR.log &


nohup python train_extraction.py --cfg_file KPGrouping --data_dir "./data/EC400K_ChartLLM/clsdata(1031)/cls" --cache_path "./data/cacheByDefaultConfig" > ./log/INFO_grouping.log 2>./log/ERROR_grouping.log &


nohup python train_extraction.py --cfg_file KPGrouping --data_dir "./data/EC400K_ChartLLM/clsdata(1031)/cls" --cache_path "./data/cache" --pretrained_model "KPDetection_best.pkl" > ./log/INFO_grouping.log 2>./log/ERROR_grouping.log &

python train_extraction.py --cfg_file KPGrouping --data_dir "./data/EC400K_ChartLLM/clsdata(1031)/cls" --cache_path "./data/cache" --pretrained_model "KPDetection_best.pkl"
python train_extraction.py --cfg_file KPGrouping --data_dir "./data/EC400K_ChartLLM/clsdata(1031)/cls" --cache_path "./data/cache" --pretrained_model "KPDetection_320.pkl"

python val_extraction.py \
--save_path evaluation \
--model_type KPGrouping \
--cache_path "./data/cache" \
--data_dir "./data/EC400K_ChartLLM/clsdata(1031)/cls" \
--trained_model_iter "best"

python val_extraction.py \
--save_path evaluation \
--model_type KPDetection \
--cache_path "./data/cache" \
--data_dir "./data/EC400K_ChartLLM/clsdata(1031)/cls" \
--trained_model_iter "best"